MediMind: An Intelligent Mental Health Monitoring System Using Speech and Text Analytics
Dhairya Korgaonkar1, Maaz Khan2, Aryan Shedge3, Riya Ankush4, Pranavkumar Badhane5
1Dhairya Korgaonkar, Artificial Intelligence and Machine Learning, Fr. Agnel Polytechnic 2Maaz Khan, Artificial Intelligence and Machine Learning, Fr. Agnel Polytechnic 3Aryan Shedge, Artificial Intelligence and Machine Learning, Fr. Agnel Polytechnic 4Riya Ankush, Artificial Intelligence and Machine Learning, Fr. Agnel Polytechnic
5Pranavkumar Badhane, Artificial Intelligence and Machine Learning, Fr. Agnel Polytechnic
Abstract - A quiet shift often happens before stress becomes overwhelming. Daily pressures build gradually, reflected in subtle changes in speech, writing, and behavior. Advances in Artificial Intelligence now allow these small signals to be understood through tools designed for Mental Health Monitoring and Preventive Mental Healthcare.
Using Speech Emotion Recognition, systems analyze tone, pitch, pauses, and rhythm to detect emotional variation. At the same time, Natural Language Processing and Sentiment Analysis examine typed words, sentence structure, and vocabulary patterns to identify shifts in mood. Together, these technologies support Mood Prediction and Stress Detection by spotting trends over time rather than reacting only during crises.
Through Machine Learning, models learn individual behavioral patterns, making predictions more personalized and accurate. What appears as normal conversation becomes structured data that reveals emotional trajectories. Integrated into a Mobile Healthcare Application, this process runs quietly in the background, offering gentle nudges, insights, or recommendations when early warning signs appear.
This approach does not replace human care; instead, it strengthens awareness. By identifying emotional changes early, AI-driven systems encourage timely reflection, healthier coping strategies, and proactive support— helping individuals respond before stress escalates into burnout or breakdown.
Key Words: Artificial Intelligence (AI), Mental Health Monitoring, Mood Prediction, Stress Detection, Speech Emotion Recognition (SER), Natural Language Processing (NLP), Sentiment Analysis, Machine Learning, Deep Learning, Behavioral Pattern Analysis, Voice Signal Processing, Emotion Classification, Mobile Healthcare Application, Digital Mental Health, Preventive Mental Healthcare, Real-time Monitoring, Predictive Analytics, Human-Computer Interaction, Psychological Well-being, AI-based Health Assistant.
